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Lecture 8: Large Cache Design I

Lecture 8: Large Cache Design I. Topics: Shared vs. private, centralized vs. decentralized, UCA vs. NUCA, recent papers. Multi-Core Cache Organizations. P. P. P. P. P. P. P. P. C. C. C. C. C. C. C. C. C. C. C. C. C. C. C. C. C. C. C. C.

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Lecture 8: Large Cache Design I

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  1. Lecture 8: Large Cache Design I • Topics: Shared vs. private, centralized vs. decentralized, • UCA vs. NUCA, recent papers

  2. Multi-Core Cache Organizations P P P P P P P P C C C C C C C C C C C C C C C C C C C C Private L1 caches Shared L2 cache Bus between L1s and single L2 cache controller Snooping-based coherence between L1s

  3. Multi-Core Cache Organizations P P P P C C C C Private L1 caches Shared L2 cache, but physically distributed Bus connecting the four L1s and four L2 banks Snooping-based coherence between L1s

  4. Multi-Core Cache Organizations P P P P C C C C P P P P C C C C Private L1 caches Shared L2 cache, but physically distributed Scalable network Directory-based coherence between L1s

  5. Multi-Core Cache Organizations P P P P C C C C D P P P P C C C C Private L1 caches Private L2 caches Scalable network Directory-based coherence between L2s (through a separate directory)

  6. Shared Vs. Private • SHR: No replication of blocks • SHR: Dynamic allocation of space among cores • SHR: Low latency for shared data in LLC (no indirection thru directory) • SHR: No interconnect traffic or tag replication to maintain directories • PVT: More isolation and better quality-of-service • PVT: Lower wire traversal when accessing LLC hits, on average • PVT: Lower contention when accessing some shared data • PVT: No need for software support to maintain data proximity

  7. Innovations for Private Caches: Cooperation • Cooperative Caching, Chang and Sohi, ISCA’06 P P P P C C C C D P P P P C C C C • Prioritize replicated blocks for eviction with a given probability; • directory must track and communicate a block’s “replica” status • “Singlet” blocks are sent to sibling caches upon eviction (probabilistic • one-chance forwarding); blocks are placed in LRU position of sibling

  8. Dynamic Spill-Receive • Dynamic Spill-Receive, Qureshi, HPCA’09 • Instead of forcing a block upon a sibling, designate caches as Spillers • and Receivers and all cooperation is between Spillers and Receivers • Every cache designates a few of its sets as being Spillers and a few of • its sets as being Receivers (each cache picks different sets for this • profiling) • Each private cache independently tracks the global miss rate on its • S/R sets (either by watching the bus or at the directory) • The sets with the winning policy determine the policy for the rest of • that private cache – referred to as set-dueling

  9. Innovations for Shared Caches: NUCA • Issues to be addressed for • Non-Uniform Cache Access: • Mapping • Migration • Search • Replication CPU

  10. Static and Dynamic NUCA • Static NUCA (S-NUCA) • The address index bits determine where the block is placed; sets are distributed across banks • Page coloring can help here to improve locality • Dynamic NUCA (D-NUCA) • Ways are distributed across banks • Blocks are allowed to move between banks: need • some search mechanism • Each core can maintain a partial tag structure so they have an idea of where the data might be (complex!) • Every possible bank is looked up and the search propagates (either in series or in parallel) (complex!)

  11. Beckmann and Wood, MICRO’04 Latency 65 cyc Data must be placed close to the center-of-gravity of requests Latency 13-17cyc

  12. Alternative Layout • From Huh et al., ICS’05: • Paper also introduces the • notion of sharing degree • A bank can be shared by • any number of cores • between N=1 and 16. • Will need support for L2 • coherence as well

  13. Victim Replication, Zhang & Asanovic, ISCA’05 • Large shared L2 cache (each core has a local slice) • On an L1 eviction, place the victim in local L2 slice (if there • are unused lines) • The replication does not impact correctness as this core • is still in the sharer list and will receive invalidations • On an L1 miss, the local L2 slice is checked before fwding • the request to the correct slice P P P P C C C C P P P P C C C C

  14. Page Coloring Bank number with Set-interleaving Bank number with Page-to-Bank CACHE VIEW Tag Set Index Block offset 00000000000 000000000000000 000000 OS VIEW Physical page number Page offset

  15. Cho and Jin, MICRO’06 • Page coloring to improve proximity of data and computation • Flexible software policies • Has the benefits of S-NUCA (each address has a unique • location and no search is required) • Has the benefits of D-NUCA (page re-mapping can help • migrate data, although at a page granularity) • Easily extends to multi-core and can easily mimic the • behavior of private caches

  16. Page Coloring Example P P P P C C C C P P P P C C C C • Awasthi et al., HPCA’09 propose a mechanism for • hardware-based re-coloring of pages without requiring copies in • DRAM memory • They also formalize the cost functions that determine the optimal • home for a page

  17. R-NUCA, Hardavellas et al., ISCA’09 • A page is categorized as “shared instruction”, “private data”, • or “shared data”; the TLB tracks this and prevents access • of a different kind • Depending on the page type, the indexing function into the • shared cache is different • “Private data” only looks up the local bank • “Shared instruction” looks up a region of 4 banks • “Shared data” looks up all the banks

  18. Rotational Interleaving • Can allow for arbitrary group sizes and a numbering that • distributes load 00 01 10 11 10 11 00 01 00 01 10 11 10 11 00 01

  19. Title • Bullet

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